Authors: Dr. Abdur Razzaque, Md. Rezaul Karim
As artificial intelligence rapidly advances, propelled by progress in neural networks (NN) and deep learning (DL), the commercialization of the Internet of Things (IoT) is reaching its peak. With increased investments in smart cities, smart healthcare, and Industrial Internet of Things (IIoT), the monetization of IoT will soon be at its zenith, necessitating the scalable processing of vast amounts of data generated by IoT devices.
This hands-on deep learning course for IoT delves deeper into IoT data, starting by introducing how DL aligns with the context to make IoT applications smarter. It then covers building deep architectures using TensorFlow, Keras, and Chainer for IoT.
Participants will learn how to train convolutional neural networks (CNN) for developing applications such as road defect detection based on images, intelligent waste separation, implementing smart lighting control through voice, and accessing smart homes provided by recurrent neural networks (RNN).
Mastery of localizing IoT applications indoors, predictive maintenance, and device positioning in a large hospital using automatic encoding, DeepFi, and LSTM networks will be achieved. Moreover, participants will learn to develop IoT applications for healthcare with enhanced IoT security.
By the end of this book, readers will have enough knowledge to effectively use deep learning to make their IoT-based applications smarter.
What You Will Learn
- Familiarize yourself with various neural network architectures and their suitability in IoT
- Understand how deep learning can enhance predictive power in your IoT solutions
- Capture and process streaming data for predictive maintenance
- Choose optimal frameworks for image recognition and indoor localization
- Analyze voice data for speech recognition in IoT applications
- Develop deep learning-based IoT solutions for healthcare
- Enhance security in your IoT solutions
- Visualize analyzed data to discover detailed insights and make accurate predictions
Who This Book Is For
This book is for IoT developers, data scientists, or deep learning enthusiasts looking to apply deep learning techniques to build intelligent IoT applications. Familiarity with machine learning, a basic understanding of IoT concepts, and some experience in Python programming will help you leverage this book to the fullest.
Table of Contents
- The Ultimate Lifecycle of IoT
- Deep Learning Architecture for IoT
- Image Recognition in IoT
- Sound/Voice/Speech Recognition in IoT
- Indoor Localization in IoT
- Physiological and Psychological States - Detection in IoT
- Security and Privacy for IoT
- Predictive Maintenance for IoT
- Deep Learning in Healthcare IoT
- What's Next: Summary and Future Directions
Course Material for the subject: Artificial Intelligence for IoT (Course Code: CE344)
Readers interested in this material are welcome to borrow it from the library or read it on-site.
Detailed Information: https://www.facebook.com/LibUIT.Fanpage/posts/pfbid02UvCVTtNWDXKix73KMdQVmaWfMaqkj3zPoFgAKKtvHTa3jMWvfBFe16EhccAN1HjCl
Hạ Băng - Media Collaborator, University of Information Technology
English version: Phan Huy Hoang
